Routing incomplete mail items

ABSTRACT

Apparatus, methods, media and code for routing a mail item are provided. A conveyor in mechanical communication with a mail item registration station may include a processor for registering a first part of the mail item. The processor may: determine that: the first part is a payment part; and a second part that corresponds to the first part is exceptional; identify a destination that corresponds to the first part; and route the first part to the destination along with an indication corresponding to the missing second part.

FIELD OF TECHNOLOGY

This application relates to processing mail items. More specifically,the application relates to routing similarly-addressed mail items todifferent destinations.

BACKGROUND OF THE INVENTION

A large organization may include multiple entities that receive physicalcommunications, such as mail, and electronic communications, such asemail. If the organization includes a sufficiently large number ofentities, the organization may have a smaller number of communicationhubs that service subsets of the entities by receiving communicationsdirected to the entities and distributing the communications to theentities. The hubs and associated subsets may be organizedgeographically, functionally, operationally or in other ways.

With a large communication volume, it may be difficult to adapt the hubsto changes in entity locations, functions and operations or othercharacteristics. Also, it may be inefficient to provide to the membersof the public, and individuals internal to the organization, currentinformation about the hub addresses for the corresponding organizationentities. Also, it may be difficult to properly distributecommunications that are insufficiently addressed or that are addressedto the wrong hub or that include erroneous address information.

It would therefore be desirable to have apparatus and methods forrouting to an organization entity insufficiently, incorrectly orerroneously addressed communications.

It also would therefore be desirable to have apparatus and methods forservicing the many entities with a smaller number of hubs or a singlehub.

BRIEF DESCRIPTION OF THE DRAWINGS

The objects and advantages of the invention will be apparent uponconsideration of the following detailed description, taken inconjunction with the accompanying drawings, in which like referencecharacters refer to like parts throughout, and in which:

FIG. 1 shows illustrative apparatus, along with an illustrative workpiece and related information, in accordance with the principles of theinvention;

FIG. 2 shows illustrative apparatus that may be used in accordance withthe principles of the invention;

FIG. 3 shows an illustrative work piece that may be processed inaccordance with the principles of the invention;

FIG. 4 shows a different view of the work piece of FIG. 3;

FIG. 5 shows another illustrative work piece that may be processed inaccordance with the principles of the invention;

FIG. 6 shows a different view of the work piece of FIG. 5;

FIG. 7 shows illustrative elements of a process in accordance with theprinciples of the invention;

FIG. 8 shows illustrative elements of another process in accordance withthe principles of the invention;

FIG. 9 shows illustrative elements of yet another process in accordancewith the principles of the invention;

FIG. 10 shows illustrative elements of still another process inaccordance with the principles of the invention;

FIG. 11 shows yet another illustrative work piece that may be processedin accordance with the principles of the invention;

FIG. 12 shows still another illustrative work piece that may beprocessed in accordance with the principles of the invention;

FIG. 13 shows still another illustrative work piece that may beprocessed in accordance with the principles of the invention;

FIG. 14 shows illustrative information that may be used in accordancewith the principles of the invention;

FIG. 15 shows illustrative elements of still another process inaccordance with the principles of the invention;

FIG. 16 shows the illustrative information of FIG. 14 along with otherillustrative information in accordance with the principles of theinvention;

FIG. 17 shows the illustrative information of FIG. 14 along with otherillustrative information in accordance with the principles of theinvention;

FIG. 18 shows the illustrative information of FIG. 14 along with yetother illustrative information in accordance with the principles of theinvention;

FIG. 19 shows still other illustrative information in accordance withthe principles of the invention;

FIG. 20 shows still other illustrative information in accordance withthe principles of the invention;

FIG. 21 shows still other illustrative information in accordance withthe principles of the invention;

FIG. 22 shows still other illustrative information in accordance withthe principles of the invention; and

FIG. 23 shows still other illustrative information in accordance withthe principles of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Apparatus, articles of manufacture including computer readable code andmedia for processing a mail item are provided. The mail item may bereceived by an organization. The mail item may be delivered to theorganization by U.S. Postal Service, electronic mail, private courier orany other form of delivery. The mail item may include an envelope. Theprocessing may include identifying an entity within the organization towhich the mail item or a part thereof can be routed. The entity may betreated as a destination. The destination may be electronically embodiedby an email address, a drop box, a physical mail box or any othersuitable electronic or physical instrument.

The mail item may include one or more parts. A mail item part may bedisposed in the envelope. The envelope may be a mail item part. The mailitem part may be a document. For example, the part may be a check, apayment coupon, an invoice, a letter or any other type of document.

The mail item part may include a segment. The segment may be an image ofsome or all of the mail item part. The segment may include information.An element of the information may be stored as an information parameter.The segment may include textual information. The segment may includecolor information. The segment may include symbolic information, such asa bar code or a QR code. The segment may include magnetically readableinformation. The segment may include geometric or pattern information.For example, the segment may include boxes such as those provided on apayment coupon in which a financial institution customer may writenumerals of a payment amount.

The segment may include a form field-identifier. The formfield-identifier may be textual information that is printed as part ofthe document. For example, on a check, “PAY TO THE ORDER OF,” or anyother suitable text, may be a form field. On a payment coupon, “MINIMUMPAYMENT DUE,” or any other suitable text, may be a form field. On aninvoice, “SUB-TOTAL,” or any other suitable text, may be a form field.

The mail item part may include physical features. The physical featuresmay include textural signals. An element of information about a physicalfeature may be stored as a physical parameter.

Table 1 sets forth illustrative parameters and exemplary data typesthereof.

TABLE 1 Illustrative parameters and data types thereof. IllustrativeParameter Name Illustrative Data Types General Parameters Received dateYYYY-MM-DD Serial no. 123456 Envelope Exterior Parameters PhysicalParameters Length 5 mm increments Width 5 mm increments Fold-Pattern A,B, C, . . . based on laser or image scan of folds and seams Size 1, 2,3, . . . based on Length and Width Color Yellow 0-256, Magenta 0-256,Cyan 0-256, Black 0-256 Addressee Window Yes or No Addressee Window 2 mmincrements Length Addressee Window Width 2 mm increments AddresseeWindow (x, y), mm, from lower origin left corner of envelope ReturnAddress Window Yes or No Return Address Window 2 mm increments LengthReturn Address Window 2 mm increments Width Return Address Window (x,y), mm, from lower origin left corner of envelope Information ParametersBar Code (linear, 2-D) Image Addressee Text segment Image Return AddressText Image segment Front text segment Image Back text segment ImageEnvelope Front Image Image Envelope Back Image Image Mail Item PartParameters Number of Mail Item 1, 2, . . . Parts (N) Part 1 Part 1Physical Parameters Part 1 Length 5 mm increments Part 1 Width 5 mmincrements Part 1 MICR Yes or No Part 1 Information Parameters Part 1Form Code String Number of Part 1 Text 1, 2, . . . Segments (P1NT) TextSegment 1 Image Text Segment 2 Image Text Segment P1NT Image Part 1Graphic Element Image Part 2 Part 2 Physical Parameters Part 2 Length 5mm increments Part 2 Width 5 mm increments Part 2 MICR (Y/N) Yes or NoPart 2 Information Parameters Part 2 Form Code String Number of Part 2Text 1, 2, . . . Segments (P2NT) Text Segment 1 Image Text Segment 2Image Text Segment P2NT Image Part 2 Graphic Element Image Part N Part NPhysical Parameters Part N Length 5 mm increments Part N Width 5 mmincrements Part N MICR Yes or No Part N Information Parameters Part NForm Code String Number of Part N Text 1, 2, . . . Segments (PNNT) TextSegment 1 Image Text Segment 2 Image Text Segment PNNT Image Part NGraphic Element Image

The article of manufacture may include non-transitory computer usablemedia that includes computer readable program code embodied therein. Thecode when executed by a processor may cause a computer to execute one ormore actions in accordance with the invention. The processor may includea processor device. The processor may be a processor device.

The media may include one or more non-transitory computer-readable mediastoring computer-executable instructions which, when executed by theprocessor on a computer system, perform methods in accordance with theinvention.

Apparatus, articles of manufacture including computer readable code andmedia for routing the mail item part are provided. The apparatus mayinclude a receiver. The receiver may be configured to receive an imageof the mail item part.

The apparatus may include a processor. The processor may be configuredto decompose a segment of the mail item part into a string vector.

The string vector may be a vector that has an element that is a textstring. The string may be a text string. The mail item part may includean image segment that includes textual information. The textualinformation may be converted into the text string by any suitablecharacter recognition approach. The string vector may include one or aplurality of text strings.

The processor may be configured to quantify a first closeness betweenthe string vector and a first library vector that corresponds to a firstmail item part destination. The processor may be configured to quantifya second closeness between the string vector and a second library vectorthat corresponds to a second mail item part destination. The processormay be configured to link to the image routing information to route themail item part to that of the first and second mail item partdestinations that corresponds to the greatest of the first and secondcloseness.

Table 2 shows illustrative vector libraries that correspond to differentmail item parts that are commonly received at different destinations. Anaggregate of mail item parts that are received by a destination mayreflect the most commonly received mail item parts at the destination.Two or more destinations that commonly receive a common kind of mailitem part may have different library vectors based on geographic,functional, operational or other differences between the destinations.

TABLE 2 Illustrative library vectors. Terms of the vectors are enclosedin slashes. The top row includes illustrative labels for the vectors.Payment- Legal- Check- Coupon- Invoice- Manifest- Order- Executive- FormForm Form Form Letter Letter Customer-Care- Library Library LibraryLibrary Library Library Letter Library /Check /Please /Attention//Lading/ /Pursuant /CEO/ /Gratitude/ No./ detach to/ and mail couponwith check payable to/ /Date/ /Check /Invoice /Ship to/ /Order/ /Chief//Thank you/ here for No./ change of mailing address or phone number//Pay To /Enter /Statement /Packag- /Court/ /Chairman/ /Outstanding/ Theall date/ ing/ Order changes Of/ on back of coupon/ /Memo/ /Account/Currency/ /Slip/ /Estate/ /Board/ /Service/ No./ /Total /Item//Received/ /Payment/ /Product/ balance/ /Minimum /Descrip- /Back /Check//Suggestion/ Payment tion/ order/ Due/ /Due /Quantity/ /Enclosed//Future/ Date/ /Enter /Qty/ /Account /Contact me/ payment No./ amount/<Box /Rate/ /Name of/ pattern> /Subtotal/ /Tax/ /Total/ /Remit/

Library vectors may include strings pertaining to tax information,estate information, brokerage information, mortgage information, creditreports or other suitable legal or business information.

The string vector may be a vector of strings. The strings may includealphanumeric characters. The alphanumeric characters may be representedby ASCII characters, encoded ASCII characters, or any other form ofcharacter or code, whether binary, hexadecimal or any other encodingscheme.

The library vector may be a vector of strings.

A “closeness” may be a quantitative measure of the similarity betweentwo vectors based on the similarity of the strings in the vectors.

A closeness between two vectors of strings may be represented as avector of closenesses between members of the two vector strings. Forexample, the closeness of string vector B to string vector A may bescored, for example, based on Equation 1.C _({tilde over (B)}-Ã)=Σ_(i=1) ^(I)min(|B _(i) −A_(j,∀jε[1,I])|^(2p))  Eqn. 1

The distance min|B_(i)−A_(j, ∀jε[1,J])|² is a minimum distance between amember of B and any of the J members of A. p is a multiplier that can begiven any appropriate value. p may be given a large value to intensifythe distribution of distances to reduce the effect of non-matchingstrings. The distance may be calculated, for example, as aDamerau-Levenshtein distance.

The first and second destinations may correspond to entities of anorganization, such as a financial institution. The entities may beaddressable such that the mail item or the mail item part may betransmitted to the entity. The destination may be a probabilisticprediction of the entity.

Routing may involve associating the mail item or mail item part with thedestination.

A routing record may include information about the mail item or the mailitem part. The routing record may include the destination. Routing mayinclude populating the routing record with the destination.

The routing record may include one or more physical parameters from themail item. The routing record may include one or more informationparameters from the mail item. One or more physical parameters may bedeleted from the routing record after the destination is inserted in therouting record. One or more information parameters may be deleted fromthe routing record after the destination is inserted in the routingrecord.

The physical parameters may be stored in a physical parameter record.The information parameters may be stored in an information parameterrecord. The physical parameter record may be logically associated with,but separate from, the routing record. The information parameter recordmay be logically associated with, but separate from, the routing record.

The apparatus may include a transmitter configured to transmit the imageto that of the first and second mail item part destinations thatcorresponds to the greatest of the first and second closeness.

The processor may be further configured to decompose into first textstrings segments from each of a plurality of first mail item parts thatwere addressed to the first destination and received by the firstdestination. The processor may be further configured to rank the firsttext strings by frequency of occurrence to form a first two-dimensionalarray. The frequency of occurrence may be a frequency of occurrence in asegment. The frequency of occurrence may be a frequency of occurrence inthe mail item part. The frequency of occurrence may be a frequency ofoccurrence in the mail item.

The processor may be further configured to eliminate rows in the firstarray that correspond to stop words. The first library may include thefirst text strings in the remaining rows. The stop words may be wordsthat are frequent and common and thus not helpful for discriminatingbetween different destinations. Stop words may be identified by a user.Stop words may be identified as words that are identified as being abovea threshold usage frequency in a population of words. The population maybe all or some of the mail items received by the organization. Thethreshold usage may be set by eliminating rows corresponding to wordsthat, based on one or more commonly available rankings of Englishlanguage word usage frequency, are used below a selected frequency.

The processor may be further configured to decompose into second textstrings segments from each of a plurality of second mail item parts thatwere addressed to the second destination and received by the seconddestination.

The processor may be configured to rank the second text strings byfrequency of occurrence to form a second two-dimensional array; andeliminate rows in the second array that correspond to stop words, thesecond library comprising the second text strings in the remaining rows.

The processor may be configured to tally a first number of matches ofstrings between the string vector and the first library. A match may bean exact match, a word-root-match, a partial match or any other suitabletype of match. When the match is a partial match, the user may select anacceptable match level. The match level may be a percentage of matchingletters between the strings. The user may select the percentage.

The processor may be configured to tally a second number of matchesbetween the string vector and the second library.

The processor may be configured to score the first number and the secondnumber. The routing information may identify the higher-scoring one ofthe first destination and the second destination.

In connection with scoring the first number, the processor may beconfigured to identify the number of text strings in the first library;identify the number of text strings in the string vector; and calculatethe multiplicative product of the first number and the reciprocal of(the number of text strings in the first library X the number of textstrings in the string vector) to arrive at a first score for the firstlibrary.

In connection with scoring the second number, the processor may beconfigured to identify the number of text strings in the second library;identify the number of text strings in the string vector; and calculatethe multiplicative product of the second number and the reciprocal of(the number of text strings in the second library X the number of textstrings in the string vector) to arrive at a second score for the secondlibrary.

Equation 2 sets forth an illustrative way to quantify score S for nthlibrary L_(n).

$\begin{matrix}{S_{n} = \frac{{number}\mspace{14mu}{of}\mspace{14mu}{matches}}{\begin{matrix}{( {{{no}.\mspace{14mu}{strings}}\mspace{14mu}{in}\mspace{14mu}{libary}\mspace{14mu} L_{n}} ) \times} \\( {{{no}.\mspace{14mu}{strings}}\mspace{14mu}{in}{\mspace{11mu}\;}{mail}\mspace{14mu}{item}\mspace{14mu}{part}\mspace{14mu}{string}\mspace{14mu}{vector}} )\end{matrix}}} & {{Eqn}.\mspace{14mu} 2}\end{matrix}$

The processor may be configured to calculate, when the first and secondlibraries are members of a plurality of N libraries: a sum of the scoresof the libraries; a first probability for the first mail item partdestination that is equal to about the first library score divided bythe sum; and a second probability for the second mail item partdestination that is equal to about the second library score divided bythe sum.

Equation 3 sets forth an illustrative way to quantify probability P fora destination when there are N libraries, each corresponding to one of Ndestinations.P _(n) =S _(n)/Σ_(n=1) ^(N) S _(n)  Eqn. 3

P_(n) may be expressed as a fraction that ranges from 0 to 1. Theprocessor may be configured to provide the routing information only ifthe greatest closeness corresponds to a probability that is at least 0.5greater than a next-greatest closeness corresponding to a differentdestination. That is, the processor will provide the routing informationonly if the maximum probability P_(max) _(N) for the N libraries isgreater than or equal to P_(next-greatest) _(N) +0.5, whereP_(next-greatest) _(N) is the probability that is, except for P_(max)_(N) , the greatest of the N probabilities.

The processor may be configured to provide the routing information onlyif the greatest closeness corresponds to a probability that is at least5 times greater than a next-greatest closeness corresponding to adifferent destination. That is, the processor will provide the routinginformation only if the maximum probability P_(max) _(N) for the Nlibraries is greater than or equal to 5×P_(next-greatest) _(N) .

The apparatus may include machine readable memory.

The processor device may be configured to: assign a destinationidentifier to an organizational entity; aggregate into an aggregatedocuments that were addressed to the entity and received by the entity;and store in the machine readable memory the destination identifier anda library that includes unique terms in the aggregate. “Unique” meanshaving one occurrence in the aggregate. The destination identifier maybe a unique destination identifier. The destination identifier maycorrespond to the entity. The library may correspond to the entity. Theentity may correspond to more than one library. For example, the entitymay have different libraries that correspond to different documenttypes.

The documents may be mail item parts that are known to have beencorrectly routed to the entity. The aggregate may include documents ofone or more types. The aggregate may include documents of only one type.

The processor device may be configured to route the mail item part tothe organizational entity only if the library quantitatively matches themail item part better than a different library matches the mail itempart.

The mail item part may be a first mail item part. The processor devicemay be configured to route a second mail item part to the organizationalentity. The first mail item part and the second mail item part mayoriginate from the same mail item. The second mail item part may matchboth the library and the different library less than a thresholdmatching value.

The unique terms may be first unique terms. The destination identifiermay be a first destination identifier. The library may be a firstlibrary. The machine readable memory may include a second destinationidentifier and a second library that includes second unique terms thatcorrespond to a second organizational entity. The first and secondlibraries may be members of a plurality of libraries that correspond todifferent organizational entities.

The processor device may be configured to define: a plurality ofclusters based on a union of the libraries; and, if: (1) the firstunique terms and the second unique terms are both closer to one of theclusters than all of the other clusters; and (2) the firstorganizational entity is a sub-entity of the second organizationalentity, a proxy destination that includes the first organizationalsub-entity and the second organizational sub-entity. The proxydestination may be electronically embodied by an email address, a dropbox, a physical mail box or any other suitable electronic or physicalinstrument.

The clusters may include k-means clusters, fuzzy clusters or any othersuitable clusters. The clusters may be defined by their means, forexample, by Equation 4.

≡min(Σ_(i=1) ^(M)Σ_((ν) _(j) _(εDC) _(i) ₎∥ν_(j) −DC _(i)∥²)  Eqn. 4

M is a number of destination clusters DC_(i) into which the N libraryvectors are divided. When M=N, and the libraries are sufficientlydifferent from each other, each library corresponds to its own cluster.When M<N and M is decreasing, similar libraries begin to merge into eachother.

v_(j) are vector offsets that correspond to each of the N libraryvectors. The offsets may be defined in any suitable manner. The v_(j)may then be assigned to the nearest DC_(i) by known cluster assignmentand mean-updating methods. When cluster assignment does not converge (ordoes not converge rapidly enough), the length, and therefore theinformation content, of the library vectors may be increased to providemore distinction between them.

DC _(i) are the mean destination cluster vectors. ∥v_(j)−DC _(i)∥ is thenorm or distance between the jth library vector and the mean vector ofthe ith destination cluster.

is a vector of means of the destination clusters that are defined by theminimization in Equation 4. Computation of the DC _(i) and assignment oflibrary vectors to the individual clusters may be accomplished by knownmethods.

The processor may be configured to select the destination for the mailitem or mail item part by finding for the mail item or mail item partthe cluster closest to the string vector obtained from the mail item ormail item part. The clusters thus model the set of destinationlibraries, but provide additional decision points when libraries are tooclose for distinction from each other. The additional decision pointsmay be proxy destinations that trap mail items or mail item parts thatwould otherwise be routed to a destination that is not easilydistinguished from another destination. The mail item or mail item partmay at the proxy destination be subject to further analysis, such as byhuman intervention. Two or more entities that correspond to the proxydestination may be provided with access to the proxy destination forreceipt of the mail item or mail item part. The two or more entities mayhave mail-sharing tools to account for acquisition of the mail item ormail item part by one of the entities and for exchange of the mail itemor mail item part between the two or more entities.

When two or more libraries that are related as entity and sub-entity onthe organizational chart merge into a cluster, the cluster may bedefined as a proxy destination. Because the library vectors of the twoor more libraries are so similar to each other, the mail item or mailitem party may be routed to the proxy destination for further processingto avoid routing error that is caused by insufficient distinctionbetween the libraries.

The processor may be configured to identify in the first unique terms aname that corresponds to the first organizational entity. The processormay be configured to route the mail item part to the firstorganizational entity instead of the proxy destination. This may allowthe processor to override a cluster-based routing decision based on anidentification of an entity or individual name.

The machine readable memory may include a second unique destinationidentifier and a second library that includes second unique terms thatcorrespond to a second organizational entity. The first and secondlibraries may be members of a plurality of libraries corresponding todifferent organizational entities. The processor device may beconfigured to define a plurality of clusters based on a union of thelibraries.

The processor device may be configured to define, if: (1) the firstunique terms and the second unique terms are both closer to one of theclusters than all of the other clusters; and (2) the firstorganizational entity is not a sub-entity of the second organizationalentity, a third organizational entity that includes both the firstorganizational entity and the second organizational entity, the thirdorganizational being a proxy destination for the first organizationalsub-entity and the second organizational sub-entity. This may provide adestination to which to route the mail item or mail item part when twoor more libraries are difficult to distinguish from each other andcorrespond to entities that are on separate branches of theorganizational chart.

The apparatus may include apparatus for routing mail items to differentdestinations. The apparatus may include a driven mail conveyor. Theconveyor may include a belt conveyor, a roller conveyor, a hydraulicconveyor or any other suitable conveyor. The conveyor may be configuredto receive a first mail item that includes a paper envelope displayingin an addressee segment an institution name and institution addressinformation. The first mail item may include a first part. The conveyormay be configured to receive a second mail item that includes a paperenvelope displaying in the addressee segment the institution name andthe institution address information and no other institution addressinformation. The second mail item may include a second part.

The processor may be configured to register in an electronic log themail item. The processor may be configured to register in the electroniclog the mail item part. Registration of the mail item or the mail itempart may include providing in a routing record a serial number. Theserial number may include a date. The serial number may be a number thatis assigned to the mail item. The serial number may be a number that isassigned to the mail item part.

The processor may be configured to: electronically route, based on afirst text string vector of the first part, the first mail item to afirst mail item destination in the institution; and electronicallyroute, based on a second text string vector of the second part, thesecond mail item to a second mail item destination in the institution,the second mail item destination being different from the first mailitem destination.

The apparatus processor may be configured to quantify a first closenessbetween the first text string vector and a first library vector thatcorresponds to the first mail item destination; and a second closenessbetween the second text string vector and a second library vector thatcorresponds to a second mail item destination. The processor may beconfigured to select the first destination based on the first closeness;and the second destination based on the second closeness.

To electronically route the first mail item, the processor may beconfigured to: tally a first number of matches between the first stringvector and the first library; tally a third number of matches betweenthe first string vector and a third library that corresponds to a thirdmail item destination; score the first number to determine a firstscore; score the third number to determine a third score; and selectthat of the first and third destinations that corresponds to a higherone of the first and third scores.

To electronically route the second mail item, the processor may beconfigured to: tally a second number of matches between the secondstring vector and the second library; tally a fourth number of matchesbetween the second string vector and a fourth library that correspondsto a fourth mail item destination; score the second number to determinea second score for the second library; score the fourth number todetermine a fourth score for the fourth library; and select that of thesecond and fourth destinations that corresponds to a higher one of thesecond and fourth scores. The scoring may be calculated based onEquation 2.

To score the first number, the processor may be configured to identifythe number of text strings in the first library; identify the number oftext strings in the first string vector; and calculate themultiplicative product of the first number and the reciprocal of (thenumber of text strings in the first library X the number of text stringsin the first string vector) to arrive at the first score.

To score the third number, the processor may be configured to: identifythe number of text strings in the third library; identify the number oftext strings in the third string vector; and calculate themultiplicative product of the third number and the reciprocal of (thenumber of text strings in the third library X the number of text stringsin the third string vector) to arrive at a the third score.

When the first and third libraries are members of a plurality of Nlibraries, the processor may be configured to calculate: a sum of thescores of the N libraries; a first probability for the first mail itemdestination that is equal to about the first library score divided bythe sum; and a third probability for the third mail item destinationthat is equal to about the third library score divided by the sum. Theprobabilities may be expressed as fractions that range from 0 to 1.

The processor may be configured to route the mail item to the firstdestination only if the first probability is a least 0.5 greater thanthe third probability. That is, the processor will so route the mailitem only if the first probability P1 is greater than or equal toP3+0.5.

The processor may be configured to route the mail item to the firstdestination only if the first probability is a least 0.5 times greaterthan the third probability. That is, the processor will so route themail item only if the first probability P1 is greater than or equal to5×P3.

The apparatus may include apparatus for routing the mail item part.

The receiver device may be configured to electronically receive: anindication that a first mail item part of the mail item is a check; anindication that a second mail item part of the mail item is a paymentcoupon; and an indication that a third mail item part of the mail itemis a message.

The processor device may be configured to: route the first mail itempart and the second mail item part to a first destination; and route thethird mail item part to a second destination that corresponds to termsin the message.

The apparatus may include a reflection detector that is in communicationwith the receiver. The reflection detector may be configured to measure:a dimension of the first mail item part, the dimension being a firstdimension; a dimension of the second mail item part, the dimension beinga second dimension; and a dimension of the third mail item part, thedimension being a third dimension.

The reflection detector may include a laser source. The reflectiondetector may include an angulating beam deflector. The beam deflectormay be a mirror. The reflection detector may include a beam intensitysensor. The beam intensity sensor may be collocated with the deflector.The reflection detector may include a back plate. The back plate mayhave a known reflectivity. The mail item may include a packagingmaterial. The material may include paper. The material may includecardboard. The material may include cotton. The material may includefiber. The material may include recycled material.

The mail item may include an overlap. For example, the mail item mayinclude an envelope that includes a closure that overlaps a face of themail item. The envelope may be a mail item part. The mail item mayinclude a first panel that overlaps a second panel.

The beam may be trained on the mail item part. The beam may be traversedacross the mail item part. The beam may form a reflective dot on themail item part. The processor may use the angle of the beam and thedistance between the deflector and the mail item part to calculate theposition of the dot relative to a corner of the mail item part. Thecorner of the envelope may be a reference corner. The detector maydetect a first reflected intensity when the dot is on an interior regionof a panel. The detector may detect a second reflected intensity whenthe dot intersects with the overlap. The detector may detect a thirdreflected intensity when the dot intersects with an edge of the mailitem part. The first, second and third intensities may be recorded asfractional intensities relative to the back plate.

The dot may be traversed along the face of the mail item part along apreprogrammed path. The path may be rectilinear. The path may besinusoidal. The path may have any suitable pattern. The first, secondand third intensities may be used to detect the one or more of thefirst, second and third dimensions. The first, second and thirdintensities may be used to detect locations of the edges of the mailitem part, the locations of the overlaps and any other suitable physicalparameters of the mail item part. The physical parameters may be used tocalculate a mail item part width, length and thickness. The physicalparameters may be used to estimate an envelope type. The envelope typemay be based on a fold pattern. Fold patterns may be labeled (e.g., “A,”“B,” “C,” . . . ) using any suitable catalog of known fold patterns.

The physical parameters may be used to estimate a document type. Theenvelope type may be based on a fold pattern.

The processor may be configured to classify: based in part on the firstdimension, the first mail item part as the check; based in part on thesecond dimension, the second mail item part as the payment coupon; and,based in part on the third dimension, the third mail item part as themessage.

The processor may be configured to classify the first mail item part bydetermining a first score indicating closeness of fit between a firststring vector from the first mail item part and a first destinationstring vector.

The processor may be configured to classify the second mail item part bydetermining a second score indicating closeness of fit between a secondstring vector from the second mail item part and a second destinationstring vector.

The processor may be configured to classify the third mail item part bydetermining a third score indicating closeness of fit between a thirdstring vector from the third mail item part and a third destinationstring vector.

The processor may be configured to: identify in an output vector of anelectronic classification network the first destination; and, toclassify the first mail item part, apply the electronic classificationnetwork to an input vector that includes: the first dimension; and astring vector from the first mail item part.

The classification network may be an artificial neural network. Theartificial neural network may be implemented on a computational platformsuch as the Neural Network Toolbox, which is available under thetrademark MATHWORKS from The Mathworks, Inc., Natick, Mass.

The input vector may be an input layer for the classification network.The output vector may be an output layer for the classification network.The classification network may include one or more hidden layers betweenthe input layer and the output layer. Each hidden layer may be a vectorthat includes one or more hidden layer cells. The hidden layer cells maysum weighted input from the input layer (or from a preceding hiddenlayer). The hidden layer may apply an activation function to the summedweighted input. The activation function may be a sigmoidal or hyperbolictangent function, but a signum or Heavyside function may be used.

The classification network may be trained in a supervised fashion, forexample, using the scaled conjugate gradient approach, to classify inputvectors as belonging to a category. For example, the classificationnetwork may be a document classification network that is trained toclassify input vectors as belonging to a document type, such as check, apayment coupon, an invoice, a letter or any other type of document. Adocument classification training data set may be used to train thedocument classification network.

The document training classification training data set may include aninput data array based on sample documents of different types. The inputdata array may have a column for each of the sample documents and a rowfor each of one or more of the physical parameters and one or more ofthe information parameters. The document classification training dataset may include an output array that indicates for each of the sampledocuments the correct known document type. The output array may have acolumn corresponding to each document and a row for each possibledocument type. The correct document type for each sample document may beindicated by the presence, in the column for the sample document, of a“1” in the row corresponding to the correct document type. Theclassification network may be applied serially to the sample documents.Input or embedded layer weights may be adjusted based on differences orgradients between the empirical output for the document and the correctoutput for the document until the classification network sufficientlycorrectly predicts document types for the sample documents. Theclassification network may then be applied to documents whose type isunknown.

The classification network may be retrained using different physical andinformation parameters to improve accuracy.

The classification network may be trained in a supervised fashion, forexample, using the scaled conjugate gradient approach, to classify inputvectors as corresponding to a destination. For example, theclassification network may be a document classification network that istrained to classify input vectors as corresponding to one of entities1400 (shown in FIG. 14), one of clusters 1600 (shown in FIG. 16), one ofclusters 1700 (shown in FIG. 17), one of clusters 1800 (shown in FIG.18) or any other suitable destination.

A destination classification training data set may be used to train thedocument classification network.

The destination training classification data set may include an inputdata array based on sample mail item parts. The input data array mayhave a column for each of the sample mail item parts and a row for eachof one or more of the physical parameters and one or more of theinformation parameters. The destination classification training data setmay include an output array that indicates for each of the sample mailitem parts the correct known destination. The output array may have acolumn corresponding to each mail item part and a row for each possibledestination. The correct destination for each sample document may beindicated by the presence, in the column for the sample document, of a“1” in the row corresponding to the correct destination. Theclassification network may be applied serially to the sample mail itemparts. Input or embedded layer weights may be adjusted based ondifferences or gradients between the empirical output for the mail itempart and the correct output for the mail item part until theclassification network sufficiently correctly predicts destinations forthe sample mail item parts. The classification network may then beapplied to mail item parts whose destination is unknown.

The classification network may be retrained using different physical andinformation parameters to improve accuracy.

To classify a received mail item part, the input vector may include oneor more of the physical parameters. The one or more physical parametersmay be from a single mail item part. The one or more physical parametersmay be from one or more mail item parts in the mail item. The inputvector may include one or more information parameters. The one or moreinformation parameters may be from a single mail item part. The one ormore information parameters may be from one or more mail item parts inthe mail item. The one or more information parameters may be part or allof a string vector. The one or more information parameters may includesome or all of more than one string vector.

The classification network may be trained to classify the input vectorinto a destination or a proxy destination. When the classificationnetwork is so trained, the input vector may include parameters from oneor more parts of a mail item.

The classification network may be trained to classify the input vectorinto a document type. When the classification network is so trained, theinput vector may include parameters from no more than one mail itempart. When the classification network is so trained, the input vectormay include parameters from no more than two mail item parts, one ofwhich is an envelope and the other of which is a mail item part frominside the envelope.

The input vector may include a string. The string may be a text string.The text string may be from the envelope surface. When the input vectorincludes two or more strings, the two or more strings may be in thestring vector. The string vector may include text from the mail itempart.

The output vector may include a value for each of a plurality of thedestinations. The value may indicate a match between the input vectorand the destination. The value may indicate NOT a match between theinput vector and the destination. The processor may provide to therouting record a destination identifier that identifies the destinationthat matches the input vector.

The destination may be a first destination. The output vector may be afirst output vector. The input vector may be a first input vector. Theprocessor may be configured to: identify in a second output vector ofthe electronic classification network the first destination. Theprocessor may be configured, to classify the third mail item part, toapply the electronic classification network to a second input vectorthat includes: the third dimension; and a string vector from the thirdmail item part.

The conveyor may be in mechanical communication with a mail itemregistration station. The processor may be disposed in the station. Theprocessor may be disposed apart from the station. The processor may bein electronic communication with the station. The processor may beconfigured to register the first part of the mail item. The processormay be configured to determine that: the first part is a payment part;and a second part that corresponds to the first part is exceptional;identify a destination that corresponds to the first part; and route thefirst part to the destination along with an indication corresponding tothe missing second part.

The processor may be configured to categorize the first part asexceptional because the first part: is not present in the mail item; orlacks a customer signature.

The processor may be configured to: apply an electronic classificationnetwork to an input vector that corresponds to the first part. The inputvector may include: a physical parameter vector that corresponds tooutput from an optical probe of the first mail item part; and a stringvector that includes a text segment from the first mail item part. Theoptical probe may include, or may be included in, the reflectiondetector.

The processor device may receive from the network an indication that thefirst mail item part corresponds to a member of a two-membercheck-coupon pair. A check-coupon pair may include a check drafted by apayor on an account in the custody of an institution that is differentfrom the organization. The payor may be a customer of the organization.The check-coupon pair may include a payment coupon. The coupon may beprepared by the organization. The coupon may include customerinformation about the customer.

The coupon may include addressee information about the organization. Thecoupon may include a form code that includes mail item information. Themail item information may include account information about an accountof the customer. The mail item information may include balanceinformation. The mail item information may include minimum paymentinformation. The mail item information may include symbolic information.For example, the mail item information may include shaped fieldinformation. The shaped field information may include a geometric shape.The geometric shape may be provided for the customer to enter paymentamount information. The payment amount information may correspond to anamount on the check. The organization may initiate the check-coupon pairby providing the coupon to the customer. The customer may complete thecheck-coupon pair by placing the coupon in an envelope along with thecheck and transmitting the pair to the organization.

The processor may be configured to identify the destination by matchingan account number on the first mail item to a customer account that isassociated with the destination.

The processor may be configured to: apply the electronic classificationnetwork to an input vector that includes: a string vector that includesa text string from the first mail item part; and receive from thenetwork an output vector indicating a match with the destination.

The apparatus may include a magnetic ink character recognition (“MICR”)reader that is configured to obtain the text segment.

The processor may be configured to set the indication to correspond tothe other member of the check-coupon pair.

The apparatus may include apparatus for applying a mailing label.

The apparatus may include the mail item receipt conveyor. The apparatusmay include the mail registration station. The mail registration stationmay include a scanning device that is configured to capture informationfrom an exterior surface of a mail item. The information may include aprinted message indicating that a customer name appearing on the mailitem does not correspond to an address on the mail item. The scanningdevice may be configured to capture a delivery error message segment ofthe surface. The processor device may be configured to identify anelectronic mail address that corresponds to a customer name in theaddressee segment of the surface.

The apparatus may include a transmitter device that is configured totransmit to the email address an electronic form for electronicallyreceiving a different address.

The processor device may be configured to route the envelope from a mailitem digitization process to a holding stage. The holding stage mayinclude a bin for holding the mail item. The holding stage may bereferred to as a mail item “orphanage” or a “dead letter office.”

The apparatus may include a receiver device that is configured toreceive the different address. The processor device may be configuredto: apply to the envelope a mailing label including the differentaddress; and route the envelope from the holding bin to the maildelivery service.

The processor device may be configured to, at the termination of a waitperiod during which the different address is not received: route theenvelope back to the mail item digitization process; and route anelectronic image of a part of the mail item to a destinationcorresponding to the part.

The processor may be configured to flag the electronic image asexceptional based on the printed message.

Illustrative embodiments of apparatus and methods in accordance with theprinciples of the invention will now be described with reference to theaccompanying drawings, which form a part hereof. It is to be understoodthat other embodiments may be utilized and structural, functional andprocedural modifications may be made without departing from the scopeand spirit of the present invention.

One of ordinary skill in the art will appreciate that the elements shownand described herein may be performed in other than the recited orderand that one or more elements illustrated may be optional. The methodsof the above-referenced embodiments may involve the use of any suitableelements, elements, computer-executable instructions, orcomputer-readable data structures. In this regard, other embodiments aredisclosed herein as well that can be partially or wholly implemented ona computer-readable medium, for example, by storing computer-executableinstructions or modules or by utilizing computer-readable datastructures.

Furthermore, such aspects may take the form of a computer programproduct stored by one or more computer-readable storage media havingcomputer-readable program code, or instructions, embodied in or on thestorage media. Any suitable computer readable storage media may beutilized, including hard disks, CD-ROMs, optical storage devices,magnetic storage devices, and/or any combination thereof. In addition,various signals representing data or events as described herein may betransferred between a source and a destination in the form ofelectromagnetic waves traveling through signal-conducting media such asmetal wires, optical fibers, and/or wireless transmission media (e.g.,air and/or space).

Processes in accordance with the principles of the invention may includeone or more features of the processes illustrated in the FIGS. For thesake of illustration, the steps of the illustrated processes will bedescribed as being performed by a “system.” The “system” may include oneor more of the features of the apparatus that are shown in FIGS. 1-2and/or any other suitable device or approach. The “system” may beprovided by the organization, another party or any other suitable party.

FIG. 1 shows illustrative apparatus 100 for routing mail item M to anentity in an organization O (not shown). Receiving dock 102 may receivemail item M. Mail item M may be addressed on its exterior toorganization O. Mail item M may not include information identifying anaddressee entity within organization O. Receiving dock 102 may receivemail item M as one of a plurality of mail items. Each of the pluralityof mail items may be addressed on its exterior to organization O. Eachmay not include information identifying an addressee entity withinorganization O. Each of the plurality may originate from a sendingparty. The sending party may send the mail item from outside theorganization. The sending party may be independent from theorganization. The sending party may send the mail item from within theorganization. The sending party may act as an agent of the organizationto send the mail item to the organization.

Mail item M may be transported to conveyor/sorter 104. Conveyor/sorter104 may size-sort and align mail item M for individual analysis.

Mail item M may be transported to reflection detector 106. Reflectiondetector 106 may register mail item with a serial number. Reflectiondetector 106 may open an electronic routing record for mail item M.Reflection detector 106 may insert the serial number in the routingrecord. Reflection detector 106 may detect physical parameters of mailitem M.

Mail item M may be transported to image grabber 108. Image grabber 108may capture an image of a front surface of mail item M. Image grabber108 may capture an image of a rear surface of mail item M. Image grabber108 may capture an image of a lateral surface of mail item M. Imagegrabber 108 may capture an image in the visible portion of theelectromagnetic spectrum. Image grabber 108 may capture an image in thenear infrared portion of the electromagnetic spectrum. An infrared imagemay identify the presence of non-paper materials in the mail item. Theinfrared image may identify the presence of water in the surface of themail item. Image grabber 108 may capture an image in the ultravioletportion of the electromagnetic spectrum. The ultraviolet image mayidentify information that is not visible by the naked eye. Theinformation may be embodied in patterns, symbols, characters or othersubject matter on the surfaces of mail item M. Image grabber 108 mayattach the image to the routing record.

Mail item M may be transported to opener 110. Opener 110 may open mailitem M and remove from mail item M one or more mail item parts PM. Ifmail item M includes an envelope, the envelope may be included as a mailitem part in PM.

Mail item parts such as mail item part P_(mi) (not shown) may betransported to reflection detector 112. Reflection detector 112 maycount the number of mail item parts that are present in mail item M.Reflection detector 112 may detect physical parameters of mail item partP_(mi). The number of mail item parts may be included in the physicalparameters. Reflection detector 112 may have one or more features incommon with reflection detector 106. Reflection detector 112 may bereflection detector 106. Reflection detector 112 may attach some or allof the physical parameters to the routing record. Reflection detector112 may assign a serial number to each of the mail item parts.Reflection detector 112 may attach the serial number to the routingrecord.

Mail item part P_(mi) may be transported to image grabber 114. Imagegrabber 114 may capture an image of a front surface of mail item partP_(mi). Image grabber 114 may capture an image of a rear surface of mailitem part P_(mi). Image grabber 114 may capture an image of a lateralsurface of mail item part P. Image grabber 114 may have one or morefeatures in common with image grabber 108. Image grabber 114 may beimage grabber 108. Image grabber 114 may attach the image to the routingrecord.

Mail item parts PM may be transported to holding stage 116. Holdingstage 116 may hold the physical mail item parts.

Segment processor 116 may decompose segments of the images into text,symbols or patterns. Segment processor 116 may include processor devicesfor recognizing characters, symbols and patterns in the segments.Segment processor 116 may attach some or all of the segments to therouting record. Segment processor 116 may derive one or more textstrings from the segments. Segment processor 116 may attach one or morethe text strings to the routing record.

Segment processor 116 may pass control of the routing record to routingengine 118. Routing engine 118 may apply one or more tests to therouting record to identify a destination in the organization to which toroute part or all of the routing record. The destination may correspondto an entity in organization map database 120.

Routing engine 118 may pass control of the routing record to electronicmail server 122. Electronic mail server 122 may transmit some or all ofthe routing record to the destination. For example, electronic mailserver 122 may transmit the routing record to one or more ofdestinations D1, D2, . . . , DD via electronic communication network124. Electronic mail server 122 may receive an electronic mail itemelectronically from electronic communication network 124. Routing engine118 may provide a routing record for the electronic mail item. Routingengine 118 may account for one or more electronic mail item parts, suchas attachments, in the electronic mail item.

Electronic mail server 122 may transmit the electronic mail item tosegment processor 116 for derivation of text strings. The electronicmail item routing record may be routed by routing engine 118 in the sameor a similar manner as routing engine 118 routes a routing record fornon-electronic mail items.

FIG. 2 is a block diagram that shows illustrative computing device 201,which may be specifically configured as a component in one or more ofthe devices shown in FIG. 1. For example, a computing device such as 201may be present in one or more of conveyor/sorter 104, reflectiondetector 106, image grabber 108, opener 110, reflection detector 112,image grabber 114, holding stage 116, segment processor 116, routingengine 118, organization chart database 120, electronic mail server 122and electronic communication network 124.

Computing device 201 may be included in any suitable apparatus that isshown or described herein. Computing device 201 may have a processor 203for controlling overall operation of the server and its associatedcomponents, including RAM 205, ROM 207, input/output module 209, andmemory 225.

Input/output (“I/O”) module 209 may include a microphone, keypad, touchscreen, and/or stylus through which a user of device 201 may provideinput, and may also include one or more of a speaker for providing audiooutput and a video display device for providing textual, audiovisualand/or graphical output. Software may be stored within memory 225 and/orstorage to provide instructions to processor 203 for enabling computingdevice 201 to perform various functions. For example, memory 225 maystore software used by computing device 201, such as an operating system217, application programs 219, and an associated database 221.Alternatively, some or all of computing device 201 computer executableinstructions may be embodied in hardware or firmware (not shown).

Computing device 201 may operate in a networked environment supportingconnections to one or more remote computers, such as terminals 241 and251. Terminals 241 and 251 may be personal computers or servers thatinclude many or all of the elements described above relative tocomputing device 201. The network connections depicted in FIG. 2 includea local area network (LAN) 225 and a wide area network (WAN) 229, butmay also include other networks. When used in a LAN networkingenvironment, computer 201 is connected to LAN 225 through a networkinterface or adapter 223. When used in a WAN networking environment,computing device 201 may include a modem 227 or other means forestablishing communications over WAN 229, such as Internet 231. It willbe appreciated that the network connections shown are illustrative andother means of establishing a communications link between the computersmay be used. The existence of any of various well-known protocols suchas TCP/IP, Ethernet, FTP, HTTP and the like is presumed, and the systemcan be operated in a client-server configuration to permit a user toretrieve web pages from a web-based server. Any of various conventionalweb browsers can be used to display and manipulate data on web pages.

Additionally, application program 219, which may be used by computingdevice 201, may include computer executable instructions for invokinguser functionality related to communication, such as email, shortmessage service (SMS), and voice input and speech recognitionapplications.

Computing device 201 and/or terminals 241 or 251 may also be mobileterminals including various other components, such as a battery,speaker, and antennas (not shown).

Terminal 251 and/or terminal 241 may be portable devices such as alaptop, cell phone, Blackberry™, or any other suitable device forstoring, transmitting and/or transporting relevant information.

Any information described above in connection with database 221, and anyother suitable information, may be stored in memory 225.

One or more of applications 219 may include one or more algorithms thatmay be used to process invoice data, assemble billing event record datasets, correlate billing events and billing event descriptors, analyzebilling events, report billing event analysis, and/or perform any othersuitable tasks related to processing invoice data.

The invention may be operational with numerous other general purpose orspecial purpose computing system environments or configurations.Examples of well known computing systems, environments, and/orconfigurations that may be suitable for use with the invention include,but are not limited to, personal computers, server computers, hand-heldor laptop devices, mobile phones and/or other personal digitalassistants (“PDAs”), multiprocessor systems, microprocessor-basedsystems, set top boxes, programmable consumer electronics, network PCs,minicomputers, mainframe computers, distributed computing environmentsthat include any of the above systems or devices, and the like.

The invention may be described in the general context ofcomputer-executable instructions, such as program modules, beingexecuted by a computer. Generally, program modules include routines,programs, objects, components, data structures, etc., that performparticular tasks or implement particular abstract data types. Theinvention may also be practiced in distributed computing environmentswhere tasks are performed by remote processing devices that are linkedthrough a communications network. In a distributed computingenvironment, program modules may be located in both local and remotecomputer storage media including memory storage devices.

FIG. 3 shows illustrative path 300, in broken line, across a frontsurface of mail item M. The reflection detector may guide the opticaldot along path 300. Reflection from the dot may provide a basis for oneor more of the physical parameters identified in Table 1.

Mail item M may include top edge TE, left edge LE, right edge RE, bottomedge BE and origin corner O. Mail item M may include informationwindows. The information windows may include boundaries that have reliefperpendicular to the plane of FIG. 3. Mail item M may includeinformation window W1. Mail item M may include information window W2.Mail item M may include information window W3.

Window W1 may encompass sender address segment Ss. Window W2 mayencompass addressee address segment SA. Window W3 may encompass formcode segment SFC.

Mail item M may include error message segment SEM. Segment SEM mayinclude an error message, such as “ADDRESSEE UNKNOWN” or “RETURN TOSENDER.” The error message may be printed on the surface of mail item M.The segments may be decomposed into text. The text may be used toidentify the mail item document type. The text may be used to identifythe destination. The segments may be processed in a manner that issimilar to that discussed below in connection with check 500.

Path 300 may include vertical sections 302. Path 300 may includehorizontal sections 304. Path 300 may cross textural features T, in itemM exterior, at points such as T1, at the top edge of mail item M, T2, atthe right side edge of mail item M, and T3, at a right boundary ofwindow W2. Path 300 may be varied to increase or decrease the arealsampling density. The reflection detector may use reflections such asthose from points T1, T2 and T3 to record physical parameters of mailitem M.

FIG. 4 shows illustrative path 400, in broken line, across back surfaceof mail item M. The reflection detector may guide the optical dot alongpath 400. Mail item M may include top edge TE, left edge LE, right edgeRE, bottom edge BE and origin corner O. Mail item M may includeoverlaps. The overlaps may have relief perpendicular to the plane ofFIG. 4. Mail item M may include overlap OL1. Mail item M may includeoverlap OL2. Mail item M may include overlap OL3.

Path 400 may include vertical sections 402. Path 400 may includehorizontal sections 304. Path 300 may cross textural features T, in itemM exterior, at points such as T4, at overlap OL1, T5, at overlap OL2,and T6, at overlap OL3. Path 400 may be varied to increase or decreasethe areal sampling density. The reflection detector may use reflectionssuch as those from points T4, T5 and T6 to record physical parameters ofmail item M. The reflections may be used to identify specific classes ofenvelopes based on the locations of points such as T4, T5 and T6.

Mail item M may include return sender address segment SRS. The segmentmay be decomposed into text. The text may be used to identify the mailitem document type. The text may be used to identify the destination.The segments may be processed in a manner that is similar to thatdiscussed below in connection with check 500.

Mail item M may include closure mechanism CM, whose presence may be aphysical parameter.

FIGS. 5-10 illustrate the decomposition of segments into text strings.The text strings may be included in a string vector. A check is used toillustrate the mail item part. It will be understood, though that themail item part may be a check, a payment coupon, a letter, an envelopeor any other type of mail item part.

FIG. 5 shows illustrative front check image 500. Check image 500 mayinclude one or more segments. Each segment may correspond to informationthat is included on the front of a check. In FIG. 5, check segments areidentified by rectangular boxes. The check segments may be identifiedusing any suitable text or pattern recognition approach. For example,check image 500 may include one or more of customer name segment 502,customer address 1 segment 504, customer address 2 segment 506, checknumber segment 508, date segment 510, payee segment 512, amount segment514, dollars segment 516, comment segment 518, signature segment 520,routing number segment 522, account number segment 524, check numbersegment 526 and any other suitable segments.

Check image 500 may include one or more form field identifiers. Eachform field identifier may correspond to a type of information that isdisplayed on the check to identify a check segment. For example, checkimage 500 may include one or more of “check number” form fieldidentifier 528, “date” form field identifier 530, “pay-to-the-order-of”form field identifier 532, “dollars” form field identifier 534, “memo”form field identifier 536 and any other suitable form field identifiers.

Origin “O” may be identified as a location on check image 500 from whichto quantify the relative locations of the segments. For example, originO may be coincident with the lower left corner of a check upon whichcheck image 500 is based. Axis “x” may run along an edge of the check.For example, axis x may run along the lower edge of the check. Axis “y”may be orthogonal to axis x and may run along an edge of the check. Forexample, axis y may run along the side edge of the check. Locations ofeach of the segments may be quantified by coordinates based on the x-and y-axes. For example, the location of a rectangular segment may bequantified as the coordinates of four corners of a rectangle. Any othersuitable scheme for quantifying segment locations may be used.

FIG. 6 shows illustrative back check image 600. Back check image 600 mayinclude one or more segments. Each segment may correspond to a type ofinformation that is included on the back of a check. In FIG. 6, checksegments are identified by rectangular boxes. For example, back checkimage 600 may include payee endorsement segment 602 and any othersuitable segments.

Back check image 600 may include one or more form field identifiers.Each form field identifier may correspond to a type of information thatis displayed on the check to identify a check segment. For example,check image 600 may include “endorse-here” form field identifier 604 andany other suitable form field identifiers.

Table 3 shows illustrative check segments and illustrative correspondingform field identifiers.

TABLE 3 Illustrative check segments and illustrative corresponding formfield identifiers. Illustrative Illustrative corresponding correspondingform field check segments identifiers Check number segment (508) Checknumber segment (526) Customer name segment (502) Customer address 1segment (504) Customer address 2 segment (506) Routing number segment(522) Account number segment (524) Payee segment (512) PAY TO THE ORDEROF (532) Payee endorsement segment ENDORSE HERE (604) (602) Payeesegment (512) PAY TO THE ORDER OF (532) Date segment (510) DATE (530)Amount segment (514) Dollars segment (516) DOLLARS (534) Comment segment(518) MEMO (536) Comment segment (518) MEMO (536) Signature segment(520)

FIG. 7 shows illustrative arrangement 700 for deriving a text stringbased on handwritten content that may be present in a segment. Forexample, handwritten content may be present in a check memo segment.Handwritten content may be present in a segment of a letter. Handwrittencontent may be present in a payment amount segment of a payment coupon.Handwritten content may be present on any type of document. For example,an organization employee or agent may receive the mail item or mailpart, write on it, and present it to the processor for rerouting withinthe organization. Handwritten content may be present in any othersuitable mail item or mail item part.

One or more of the elements of arrangement 700 may include one or moreof the features shown in FIG. 5. Arrangement 700 may include meta-dataprocessing engine 702. Meta-data processing engine 702 may receive acheck image, such as front check image 500 (shown in FIG. 5) or backcheck image 600 (shown in FIG. 6), from check image server.

Arrangement 700 may include calibration data input module 704.Calibration data input module 704 may receive from a handwriting sample.The handwriting sample may be from a customer of the organization. Thehandwriting sample may be from an employee of the organization.

The handwriting sample may correspond to printed character referencetext. The customer may provide the printed character reference text.Meta-data processing engine 702 may provide the printed characterreference text. The printed character reference text may be derived fromprinted character text on the check.

Handwriting may include cursive or script information written by hand orprinted by machine. Printed character text may be block-style lettersthat are written by hand or printed by machine.

The handwriting sample may be a signature. The signature may be from asignature card that the customer signed to obtain signatory authorityfor an account. The printed character reference text may be prepared inconnection with the signature.

The handwriting sample may be from a check image such as front checkimage 500 (shown in FIG. 5) or back check image 600 (shown in FIG. 6) orfrom any other type of mail item part. The corresponding printedcharacter reference text may be provided by a handwriting decodingalgorithm, a financial institution agent, the customer or any othersuitable system or individual.

The corresponding printed character reference text may be obtained froma check image such as front check image 500 (shown in FIG. 5) or backcheck image 600 (shown in FIG. 6). For example, the printed characterreference text may be obtained from segment 602 of check image 600. Someor all of the content of segment 602 may correspond to some or all ofthe content of segment 512 of check image 500. When the document is apayment coupon, the printed character reference text may be obtained,for example, from a minimum payment amount numerical field.

Handwriting library 706 may store the handwriting samples and thecorresponding printed character reference text. Handwriting library 706may store handwriting samples and corresponding printed characterreference text for a plurality of accounts. Handwriting library 706 maystore, in connection with one or more of the handwriting samples, anumerical function or functions that quantitatively characterize thehandwriting sample. Handwriting library 706 may store handwritingsamples and corresponding printed character reference text for aplurality of organization correspondents. One or more of thecorrespondents may be an organization customer.

A handwriting sample may be collected from the organization customerupon opening of an account. The handwriting sample may include a phrase.The phrase may be a letter. The phrase may be word. The phrase may be asequence of words. The phrase may be a sentence. The phrase may be anysuitable unit of writing. The phrase may include letters that are knownto the institution. The institution may store the phrase as a referencephrase. The institution may provide the phrase to the customer. Thecustomer may copy the phrase in cursive handwriting. The customer maycopy the phrase in printed handwriting. The handwriting sample mayinclude all capital letters. The handwriting sample may include alllower case letters. The handwriting sample may include both upper caseand lower case letters. The handwriting sample may be paired in thelibrary with reference phrase. The reference phrase may be used toassociate some or all of the handwriting sample with the known letters.

The institution may provide the customer with an opportunity to enrollin a handwriting translation program. The program may involve some orall of the features of arrangement 700. The institution may provide thecustomer with an opportunity to open an account that involves some orall of the features of arrangement 700. The institution may provide thecustomer with an opportunity to provide a handwriting sample at the timeof enrollment in the program or at the time of opening the account. Theinstitution may provide the customer with an opportunity to provide ahandwriting sample at any suitable time. For example, the institutionmay provide a web site that includes one or more reference phrases andinstructs the customer how to provide the handwriting sample. Thecustomer may provide the handwriting sample by writing the phrase onpaper and scanning and transmitting the handwriting sample to theinstitution. The customer may provide the handwriting sample via stylusand tablet such that the handwriting sample is directly electronicallytransmitted to the institution via a customer device. The customer mayprovide the handwriting sample to the institution at a brick-and-mortarfinancial services center.

Meta-data calibration data server 708 may serve handwriting samples tometa-data processing engine 702. Meta-data calibration data server 708may serve printed character reference text that corresponds to thehandwriting samples to meta-data processing engine 702.

Meta-data calibration data server 708 may include a processor (notshown) that compares segment content to a library handwriting sample.For example, the processor may receive segment content from meta-dataprocessing engine 702. The processor may generate one or more numericalfunctions that correspond to the check segment content. The processormay quantitatively compare the one or more check segment contentnumerical functions to the one or more handwriting sample numericalfunctions. The processor may thus identify a handwriting sample thatmatches or partially matches the segment content. The match or partialmatch may be based on an objective function that indicates a degree oflikeness between the handwriting sample and the segment content.

If a match or partial match is found, meta-data calibration data server708 may provide to meta-data processing engine 702 the printed characterreference text that corresponds to the handwriting sample.

Arrangement 700 may include text string storage 705. Informationparameter storage 705 may include one or more records of informationparameters from the mail item part.

FIG. 8 shows illustrative process 800 for identifying a text string.Process 800 may begin at step 802. At step 802, the system may receivean image. At step 804, the system may decompose the image to isolate asegment. At step 806, the system may translate content of the segment.At step 808, the system may store translated content in a text stringrecord.

FIG. 9 shows illustrative process 900 for decomposing the image. Thesystem may execute one or more of the steps of process 900 in connectionwith the execution of step 804 of process 800 (shown in FIG. 8). Process900 may begin at step 902. At step 902, the system may formulate a labelestimate for a segment based on check X-Y coordinates, such as thosediscussed in connection with FIG. 6. A segment may be isolated using anysuitable object-identification algorithm.

For example, the system may estimate that segment 512 (shown in FIG. 5)is a payee segment based on values of its x and y coordinates. Ycoordinates near or above the y midpoint of the check and x coordinatesthat span from near the left margin of the check to a central rightportion of the check may be associated with payee segments.

At step 904, the system may read a form field identifier. The form fieldidentifier associated with payee segment 512 is form field identifier532 (“PAY TO THE ORDER OF:”). At step 906, the system may score acomparison of label. The system may perform character recognition on theform field identifier.

At step 906, the system may score a comparison of the label estimate toform field identifier 532. The system may estimate the likelihood thatthe characters of form field identifier 532 correspond to a payeesegment. Any suitable index of the likelihood may be used to score thecomparison.

At step 908, the system may compare the score to a threshold. Thethreshold may include, for example, a confidence interval or limit.

At step 910, the system may determine if the score is satisfactory. Ifthe score does not meet or exceed the threshold, process 900 maycontinue at step 902 to re-estimate the segment label. If the score doesmeet or exceed the threshold, process 900 may continue at step 912. Atstep 912, the system may label the segment. For example, the system maylabel segment 512 of check image 500 (shown in FIG. 5) as “PAYEE.” Thecontent of segment 512 may be associated with the “PAYEE” label intransaction record 100 (shown in FIG. 1).

FIG. 10 shows illustrative process 1000 for translating segment content.The system may execute one or more of the steps of process 1000 inconnection with the execution of step 806 of process 800 (shown in FIG.8). Process 1000 may begin at step 1002. At step 1002, the system mayinput segment content to a handwriting decoding application. Anysuitable handwriting decoding application may be used. For example, thesystem may use. The handwriting decoding application may outputestimated characters that corresponds to the segment content.

At step 1004, the system may determine whether to confirm the estimatedcharacters. For example, the system may include a switch that configuresthe system to confirm the estimated characters. The switch may beconditional. For example, the switch may be set for confirmation of onlysegments that are associated with selected label. For example, thesystem may confirm only estimated characters that correspond to payeesegment content. The switch may be set for confirmation of only selectedestimated characters. For example, the system may confirm only estimatedcharacters that correspond to selected payees. The selected payees maybe selected based on past errors in estimation of the payee name. Thepast errors may be identified by the system. The past errors may beidentified by the customer.

If at step 1004 the system determines to not confirm the handwritingdecode application output, process 1000 may continue at step 1020. Atstep 1020, the system may store the estimated characters in atransaction record such as transaction record 100 (shown in FIG. 1).When the estimated characters are based on segment 532 of check image500 (shown in FIG. 5), the estimated characters may be “PAYEE, INC.” Thecharacters “PAYEE, INC.” may therefore be stored in payee field 106 oftransaction record 100.

At step 1022, the system may update handwriting library 706 by appendingthe content of segment 532 and the estimated characters “PAYEE, INC.” tolibrary 706.

At step 1024, the system may receive from a customer a segment contentcorrection. For example, the system may provide to the customer a viewof the segment content and a view of the estimated characters thatcorrespond to the segment content. The customer may provide to thesystem a correction of the estimated characters. If the customerprovides the correction, process 1000 may continue at step 1022.

If at step 1004 the system determines to confirm the handwriting decodeapplication output, process 1000 may continue at step 1006. At step1006, the system may identify a first handwriting sample in handwritinglibrary 706 (shown in FIG. 7).

At step 1008, the system may identify a second handwriting sample fromhandwriting library 706. The system may select, from the first andsecond handwriting samples, that handwriting sample that most closelymatches the input segment content. The system may use any suitablepattern recognition algorithm and any suitable quantitative approach toselect the most closely matching handwriting sample.

At step 1010, the system may score a comparison between the handwritingdecode application output generated in step 1002 and the most closelymatching handwriting library printed character reference text.

At step 1012, the system may determine whether the score of step 1010 issatisfactory. If the score is satisfactory, process 1000 may continue atstep 1020, which is described above along with illustrative subsequentsteps.

If at step 1012, the system determines that the score of step 1019 isnot satisfactory, process 1000 may continue at step 1014. At step 1014,the system may score a comparison of the decode application output todecode application output for a different segment in the same mail itemor mail item part. For example, if the system is not satisfied by ascore comparing decode application output for a first segment to alibrary sample or samples, the system may decode a second segment fromthe same mail item or mail item part, whether or not the second segmenthas been translated and stored in the library. The system may translatethe second segment using illustrative steps of process 1000. If thesecond segment translates well, for example, based on a score such asthat in step 1010, the system may compare the first segment's decodeapplication output to the translation of the second segment. The systemmay score the comparison.

The second segment may include printed character text. For example, theprinted character text may be present in a segment such as segment 602in back check image 600 (shown in FIG. 6). Because segment 602 mayinclude payee information, and may include printed character text, thesystem may use a decode application output based on segment 602 contentas a basis for confirming the decoding of content from payee segment 512in front check image 500 (shown in FIG. 5).

The system may perform sub-segment pattern analysis. The system mayidentify a handwritten letter of the alphabet based on a correspondingprinted character reference text. The pattern of the handwritten lettermay then be used to identify a letter in a segment that requiresdecoding.

If the score is satisfactory, process 1000 may continue at step 1020,which is described above along with illustrative subsequent steps.

If the score is unsatisfactory, process 1000 may continue at step 1018.At step 1018, human intervention may be initiated. The humanintervention may involve a financial institution agent. The agent may bean employee, an appointee, a partner a contractor or any other suitableagent. The agent may view the segment content and provide the systemwith a translation into printed characters.

Process 1000 may continue at step 1020, which is described above alongwith illustrative subsequent steps.

FIGS. 11-13 illustrate document segments and form fields that may bedecomposed into text strings in a manner that is similar to the mannerin which check 500 segments may be decomposed as shown and described inconnection with FIGS. 5-10.

FIG. 11 shows illustrative payment coupon 1100. Payment coupon 1100 mayinclude one or more of detach-here segment 1102,change-of-address-check-box segment 1104, form code segment 1106,customer-name segment 1108, customer-address-1 segment 1110,customer-address-2 segment 1112, customer-or-account-identifier-bar-codesegment 1114, account-number segment 1116, balance segment 1118,minimum-payment-amount segment 1120, due-date segment 1122,amount-enclosed segment 1124, organization-name segment 1126,organization-address-1 segment 1128, organization-address-2 segment1130, organization-bar-code-segment 1132 and any other suitable segment.

FIG. 12 shows illustrative letter 1200. Letter 1200 may include returnaddress segment 1202, individual-name segment 1204, organization-namesegment 1206, organization-address-1 segment 1208,organization-address-2 segment 1210, return-address-1 segment 1212,return-address-3 segment 1214, caption segment 1216, letter-body segment1218, salutation segment 1220, message segment 1222, signature-blocksegment 1224, correspondent-signature segment 1226, correspondent name1228, return-address-4 segment 1230 and any other suitable segment.

FIG. 13 shows illustrative invoice 1300. Invoice 1300 may includeorganizational-identity segment 1302. Segment 1302 may includeentity-identifier form field 1304, individual-identifier form field1306, organization-address form field 1308, organization-address-1segment 1310, organization-address-1 segment 1312 and any other suitableform fields or segments. Invoice 1300 may include invoice-generalsegment 1314. Segment 1314 may include invoice-no. form field 1316,currency-identifier form field 1318, statement-date form field 1320,invoice-no. segment 1322, currency-indicator segment 1324, date segment1326 and any other suitable form fields or segments.

Invoice 1300 may include header segment 1328. Segment 1328 may includeitem form field 1330, symbol form field 1332, description form field1334, quantity form field 1336, rate form field 1338, subtotal formfield 1340, tax form field 1342, total form field 1344, item-identifiersegment 1346, item-symbol segment 1348, which may identify a type ofmerchandise, item-description segment 1350, quantity segment 1352, ratesegment 1354, subtotal segment 1356, tax segment 1358, total segment1360 and any other suitable form field or segment.

Invoice 1300 may include total form field 1362. Invoice 1300 may includetotal-amount segment 1364. Invoice 1300 may includeremittance-instruction segment 1366.

FIG. 14 shows illustrative organization chart 1400 for the organization.Organization chart 1400 includes relationship lines such as 1402 thatshow relationships between entities, such as entities 1404, 1408, 1410,1412, 1414 and 1416. Level 1 entities are the highest level entities.Level 4 entities are the lowest level entities. Level 4 entities mayinclude individual organization associates. The organization may haveany number of levels of entities.

One or more of the entities in the chart may be a destination (“D_(n),”n=1 . . . N, for N destinations) for the mail item or mail item part. Adestination identifier may be assigned to one or more of the entities inthe chart. The destination identifier may identify the level at whichthe entity is placed. The destination identifier may distinguish theentity from other entities at the same level and under the samesuper-entity. For example, destination identifier 1406 may identifyCUSTOMER CARE entity 1404. CUSTOMER CARE entity 1404 is the thirdentity, under super-entity BUSINESS, at Level 2. Destination identifier1406 is therefore “L1E3/L2E3.” The rightmost portion (“L2E3”) ofidentifier 1406 identifies the entity as being a third entity (“E3”) atLevel 2 (“L2”). The remainder (“L1E3/”) identifies super-entity BUSINESSas the super-entity that includes CUSTOMER CARE. Destination identifier1406 is thus unique for the organization. Destination identifierscorresponding to some or all of the rest of the entities in theorganization may be provided (but, for the sake of clarity, are not allshown).

A library vector may be associated with one or more of the destinationsin chart 1400.

FIG. 15 shows illustrative process 1500 for quantifying probability Pnthat a mail item or mail item part is “belongs” (or should be routed) toa destination in chart 1400. Process 1500 may begin at step 1502. Atstep 1502, the system may decompose a mail item part segment intostrings. The strings may be arranged in a string vector. At step 1504,the system may retrieve a library vector for one or more of thedestinations in chart 1400. At step 1506, the system may count thenumber of strings in the string vector that match a string in thelibrary vector for library n. At step 1508, the system may calculatescore Sn, which indicates the closeness of matching between the stringvector and library vector L_(n), for example, using Equation 2. At step1510, the system may calculate probability Pn, which indicates theprobability that destination D_(n) is the correct destination for themail item part, for example, using Equation 3. The mail item part may berouted to the destination D_(n) having the highest probability Pn.

FIG. 16 shows organizational chart 1400 (shown in FIG. 14) overlain byclusters 1600 (including, for example, clusters 1602, 1604, 1606, 1608and 1610) that may be defined, for example, using Equation 4, when M=N.Each of the N destinations Dn corresponds to its own cluster Cn, whichis one of M clusters. The mean values of the clusters may be used asproxy libraries for the destinations. In Equation 3, therefore,closeness between the string vector and the libraries may be calculatedusing the mean cluster values instead of the library values and the mailitem part may be routed to the destination corresponding to the closestmean cluster to the mail item part.

FIG. 17 shows organizational chart 1400 (shown in FIG. 14) overlain byclusters 1700 (including clusters 1702 and 1704) that may be defined,for example, using Equation 4, when M is selected to be less than N.When M is selected to be less than N, the destinations must be “fit”into a small number of clusters than the number of destinations, soproxy destinations may merge into each other. For example, cluster 1702has subsumed clusters 1602, 1604, 1606 and 1608 of clusters 1600 (shownin FIG. 16). Cluster 1702 may become a proxy destination. Cluster 1702may define a proxy destination that corresponds to entities 1408, 1410,1412 and 1414. The mail item part may be routed to the cluster 1702proxy destination. The mail item part may be further routed afterreceipt at the proxy destination.

The cluster 1702 proxy destination encompasses entities that “extend”from a single branch of organization chart 1400.

FIG. 18 shows organizational chart 1400 (shown in FIG. 14) overlain byclusters 1800 that may be defined, for example, using Equation 4, when Mis selected to be less than N (and different from the M selected forclusters 1700 (shown in FIG. 17). Cluster 1802 has subsumed clusters1606 and 1610 of clusters 1600 (shown in FIG. 16). Cluster 1802 maybecome a proxy destination. Cluster 1802 may define a proxy destinationthat corresponds to entities 1412 and 1416. The mail item part may berouted to the cluster 1802 proxy destination. The mail item part may befurther routed after receipt at the proxy destination.

The cluster 1802 proxy destination encompasses entities that “extend”from multiple branches of organization chart 1400.

FIG. 19 shows illustrative trained classification network 1900.Classification network 2000 may include input layer 1902, hidden layer1904 and output layer 1906. Input layer 1902 may correspond to an inputvector. Hidden layer 1904 may be one of several hidden layers. Outputlayer 1906 may correspond to an output vector.

FIG. 20 shows illustrative input vectors 2002, 2004 and 2006 for threedifferent mail parts whose document type is unknown, which are preparedfor analysis by a classification network trained to classify documentsinto document types based on physical parameters 2008.

FIG. 21 shows hypothetical output vectors 2102, 2104 and 2106,corresponding to input vectors 2002, 2006 and 2008, respectively. In theoutput vectors, a “1” indicates a match and a “0” indicates a lack of amatch. Mail item part 1 is thus hypothetically classified as a paymentcoupon, mail item part 2 is thus classified as a check, and mail itempart 3 is thus hypothetically classified as a letter.

FIG. 22 shows illustrative input vectors 2202 and 2204 for two differentmail items whose destination with the organization is unknown. The inputvectors are prepared for analysis by a classification network that istrained to classify mail items into destinations based on parameters2206. The input vectors are arranged such that all of the mail itemparts of the mail items will be classified into a single destination. Byapplying the classification network to each mail item part individually,the mail item parts from the single mail item could be classified intodifferent destinations.

Length parameter 2208 indicates that the two mail items have about thesame length. Width parameter 2210 indicates that the two mail items haveabout the same width. fold-pattern parameter 2212 indicates that the twomail items have different fold patterns. Color parameter 2214 indicatesthat the two mail items are both white. Window parameters 2216 indicatethat the addressee windows of the two mail items are similar. Addresseetext parameter 2218 indicates that “ORGANIZATION NAME” appears in anaddressee segment of both mail items and that no further difference inthe addressee segments.

Document type parameter 2220 indicates that both mail items include apayment coupon. Form code parameter 2222 shows a slight differencebetween the form codes present in the two mail items.

Probability parameters 2224 may be based on Equation 3, for example.Probabilities for any destinations or proxy destinations may beincluded. Probability parameters 2224 indicate that mail item 1 is moreprobably associated with destination L1E1/L2E[1]/L3E2 (parameter 2226,and see FIG. 14) and mail item 2 is more probably associated withdestination L1E1/L2E[2]/L3E2 (parameter 2228, and see FIG. 14). (Squarebrackets provided to emphasize the distinction between the twodestinations.)

FIG. 23 shows hypothetical output vectors 2302, 2304, corresponding toinput vectors 2202 and 2204, respectively. In the output vectors, a “1”indicates a match and a “0” indicates a lack of a match. Mail item 1 isthus hypothetically classified to destination L1E1/L2E[1]/L3E2. Mailitem 2 is thus classified to L1E1/L2E[2]/L3E2. The processor may routethe mail items accordingly.

Thus, apparatus, methods, articles of manufacture including computerreadable code, and media for processing a mail item have been provided.Persons skilled in the art will appreciate that the present inventioncan be practiced by other than the described embodiments, which arepresented for purposes of illustration rather than of limitation. Thepresent invention is limited only by the claims that follow.

What is claimed is:
 1. Apparatus for routing a mail item, the apparatuscomprising: a conveyor in mechanical communication with a mail itemregistration station that includes a processor for registering a firstpart of the mail item, wherein the processor is configured to: determinethat: the first part is a payment part; the first part is a member of atwo-member pair comprising the first part and a second part, wherein thesecond part comprises identification information; and the second part isexceptional; identity a destination corresponding to the first part;transmit the destination corresponding to the first part to a labelingapparatus; and route the mail item based on the identified destinationcorresponding to the first part via the conveyor along with anindication that the first part is a member of a two-member paircomprising the first part and the second part; and labeling apparatus incommunication with the processor and configured to apply a mailing labelto the mail item, the mailing label comprising the destinationcorresponding to the first part.
 2. The apparatus of claim 1 wherein theprocessor is further configured to categorize the first part asexceptional because the first part: is not present in the mail item; orlacks a customer signature.
 3. The apparatus of claim 1 wherein theprocessor is further configured to: apply an electronic classificationnetwork to an input vector that corresponds to the first part, the inputvector including: a physical parameter vector that corresponds to outputfrom an optical probe of an envelope associated with the mail item; aphysical parameter vector that corresponds to output from an opticalprobe of the first mail item part; and a string vector that includes atext segment from the first mail item part; and receive from the networkan indication that the first mail item part corresponds to a member of atwo-member check-coupon pair.
 4. The apparatus of claim 1 wherein theprocessor is further configured to match an account number on the firstmail item to a customer account to identify the destination.
 5. Theapparatus of claim 1 wherein the processor is further configured to:apply an electronic classification network to an input vector thatincludes: a physical parameter vector that corresponds to output from anoptical probe of an envelope associated with the mail item; a physicalparameter vector that corresponds to output from an optical probe of thefirst mail item part; a text string vector that includes a text stringfrom the first mail item part; and a probability parameter indicating aprobability that the first mail item part is associated with thedestination; and receive from the network an output vector indicating amatch with the destination, the output vector determined based on theinput vector.
 6. The apparatus of claim 3 further comprising a magneticink character recognition (“MICR”) reader configured to obtain the textsegment.
 7. The apparatus of claim 3 wherein the processor is furtherconfigured to set the indication to correspond to the other member ofthe check-coupon pair.
 8. An article of manufacture comprising anon-transitory computer usable medium having computer readable programcode embodied therein, the code when executed by one or more processorscausing a computer associated with an organization to route a physicalmail item, the computer readable program code in the article comprising:computer readable program code that when executed causes the computer toregister for the mail item a first part; computer readable program codethat when executed causes the computer to determine that: the mail itemis a payment mail item; the first part is a member of a two-member paircomprising the first part and a second part, wherein the second partcomprises information identifying the mail item; and the second part isexceptional; computer readable program code that when executed causesthe computer to identify a destination that corresponds to the firstpart; and computer readable program code that when executed causes thecomputer to route the physical mail item via a conveyor apparatus basedon the identified destination that corresponds to the first part alongwith an indication that the first part is a member of a two-member paircomprising the first part and the second part.
 9. The article of claim 8further comprising computer readable program code that when executedcauses the computer to categorize the first part as exceptional becausethe first part: is not present in the mail item; or lacks a customersignature.
 10. The article of claim 8 further comprising: computerreadable program code that when executed causes the computer to apply anelectronic classification network to an input vector that includes: aphysical parameter vector that corresponds to output from an opticalprobe of an envelope associated with the mail item; a physical parametervector that corresponds to output from an optical probe of the firstmail item part; and a string vector that includes a text segment fromthe first mail item part; and computer readable program code that whenexecuted causes the computer to receive from the network an indicationthat the first mail item part corresponds to a member of a two-membercheck-coupon pair.
 11. The article of claim 8 further comprisingcomputer readable program code that when executed causes the computer tomatch an account number on the first mail item to a customer account.12. The article of claim 8 further comprising: computer readable programcode that when executed causes the computer to apply an electronicclassification network to an input vector that includes: a physicalparameter vector that corresponds to output from an optical probe of anenvelope associated with the mail item; a physical parameter vector thatcorresponds to output from an optical probe of the first mail item part;a text string vector that includes a text string from the first mailitem part; and a probability parameter indicating a probability that thefirst mail item is associated with the destination; and computerreadable program code that when executed causes the computer to receivefrom the network an output vector indicating a match with thedestination, the output vector determined based on the input vector. 13.The article of claim 10 further comprising a magnetic ink characterrecognition (“MICR”) reader configured to obtain the text segment. 14.The article of claim 10 further comprising computer readable programcode that when executed causes the computer to set the indication tocorrespond to the other member of the check-coupon pair.
 15. One or morenon-transitory computer-readable media storing computer-executableinstructions which, when executed by one or more processors of acomputer system, perform a method for routing a physical mail item, themethod comprising: registering, by the one or more processors, for themail item, a first part; determining, by the one or more processors,that: the mail item is a payment mail item; the first part is a memberof a two-member pair comprising the first part and a second part,wherein the second part comprises information identifying the mail item;and the second part is exceptional; identifying, by the one or moreprocessors, a destination that corresponds to the first part; androuting, by the one or more processors via a conveyor apparatus, themail item based on the identified destination that correspond to thefirst part along with an indication that the first part is a member of atwo-member pair comprising the first part and the second part.
 16. Themedia of claim 15 wherein, in the method, the determining includescategorizing, by the one or more processors, the first part asexceptional because the first part: is not present in the mail item; orlacks a customer signature.
 17. The media of claim 15 wherein thedetermining includes: applying, by the one or more processors, anelectronic classification network to an input vector that includes: aphysical parameter vector that corresponds to output from an opticalprobe of an envelope associated with the mail item; a physical parametervector that corresponds to output from an optical probe of the firstmail item part; and a string vector that includes a text segment fromthe first mail item part; and receiving, by the one or more processors,from the network an indication that the first mail item part correspondsto a member of a two-member check-coupon pair.
 18. The media of claim 15wherein the identifying comprises matching, by the one or moreprocessors, an account number on the first mail item to a customeraccount.
 19. The media of claim 15 wherein the identifying comprises:applying, by the one or more processors, an electronic classificationnetwork to an input vector that includes: a physical parameter vectorthat corresponds to output from an optical probe of an envelopeassociated with the mail item; a physical parameter vector thatcorresponds to output from an optical probe of the first mail item part;a text string vector that includes a text string from the first mailitem part; and a probability parameter indicating a probability that thefirst mail item is associated with the destination; and receiving fromthe network an output vector indicating a match with the destination,the output vector determined based on the input vector.
 20. The media ofclaim 17 further comprising obtaining, by a magnetic ink characterrecognition (“MICR”) reader, the text segment.
 21. The media of claim 17wherein the routing includes setting, by the one or more processors, theindication to correspond to the other member of the check-coupon pair.